code: def test_predict_with_ndarray_distributed(self):
      keras_model = self.create_model()
      model = KerasModel(keras_model)
  
      x, y = self.create_training_data()
  
      results_pre = model.evaluate(x, y)
  
      pred_y = np.argmax(model.predict(x, distributed=True), axis=1)
      acc = np.average((pred_y == y))
      print(results_pre)
      assert np.square(acc - results_pre["acc"]) < 0.000001
  
imports: import pytest
  from test.zoo.pipeline.utils.test_utils import ZooTestCase
  import tensorflow
  import numpy
  import os
  from zoo.tfpark import KerasModel, TFDataset, TFOptimizer
label_desc: Use image node_id 19 for calling the TestTFParkModel obj's underlying member method code with example usage: obj.test_predict_with_ndarray_distributed() without return types